TO THE CONSTERNATION of his colleagues, Mark Eisner once told areporter that his discipline "is probably the most important fieldnobody's ever heard of." Indeed, it's not one that's likely to come upat dinner parties.

"I've been explaining for 40 years what operations research is," saysEisner, who is associate director of the school of operations researchand industrial engineering at Cornell University. He defines O.R. as"the effective use of scarce resources under dynamic and uncertainconditions."

That may sound arcane, but it's pretty much the problem of living --and certainly the central problem of economic life. O.R. isn'teconomics, however, though most economists have some O.R. training.It's applied mathematics. Since its origins in World War II to itsrecent resurgence fueled by the explosion in raw computing power, O.R.has developed analytical models of the tradeoffs and uncertaintiesinvolved in problems ranging from inventory management to policedeployment, from scheduling sports leagues to determining how manypeople to call for jury duty.

Taking the kids to Disney World this summer? Operations research willbe your invisible companion, scheduling the crews and aircraft,pricing the plane tickets and hotel rooms, even helping to designcapacities on the theme park rides. If you use Orbitz to book yourflights, an O.R. engine sifts among millions of options to find thecheapest fares. If you get directions to the hotel from MapQuest,another O.R. engine spits out the most direct route. If you shipsouvenirs home, O.R. tells UPS which truck to put the packages on,exactly where on the truck the packages should go to make them fastestto load and unload, and what route the driver should follow to makehis deliveries most efficiently.

At the park, O.R. can even let you skip the lines for the most popularrides. For Epcot's new Mission Space ride, for instance, you can joina "virtual queue" using the FastPass system introduced in 1999. Acomputer issues a pass that tells you when to claim your spot at thefront of the line. But it doesn't just tell you to come back after anarbitrary length of time, say, an hour and 15 minutes. Rather, tocalculate a return time for each guest in the face of constantlyshifting waiting times, the virtual queue's software takes intoaccount how many people are standing in the real line, how many arealready in the virtual queue, and how many of each group the parkwants to admit each time the ride opens up.

"That's the O.R. piece," says Irv Lustig, manager of technicalservices for ILOG Direct, a software and O.R. consulting companyheadquartered in Gentilly, France, and Mountain View, Calif. Hevisited the parks in February to see how Disney uses O.R. and woo thecompany as an ILOG client.

After decades in which the field's progress was mostly theoretical,computers have finally gotten powerful enough to collect the data anddeliver the problem-solving solutions that O.R. has been promisingsince the heady days of the New Frontier. Beginning in the 1980s, whenAmerican Airlines demonstrated that airlines could save billions ofdollars using O.R. techniques to design their schedules, O.R. hasbecome an increasingly important, though largely invisible,contributor to rising productivity.

"What we talked about when I was a young graduate student are stillthe things that we talk about now, except then we could only talkabout them," says Jack Muckstadt, a Cornell professor who entered thefield in the early 1960s. "Now we can actually do them."

Indeed, when Irv Lustig got his doctorate in operations research fromStanford in 1987, his thesis was controversial. Although it had theobligatory theorems and proofs, it also included computational workthat some members of Stanford's O.R. department (now its department ofmanagement science and engineering) thought too lowbrow.

By contrast, he says, today O.R. students who want to just do theoryhave a hard time. "Everybody wants to know, `What does it mean on acomputer?"' says Lustig, whose work has included creating the NationalFootball League's schedule. "That's a big culture change."

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O.R. started as a way of bringing scientific thinking to the complexproblems of warfare: How do you find enemy submarines? How manybombers do you need to make sure a critical target is destroyed? When,where, and with how many troops and what equipment should you make anamphibious landing?

In World War II, scientists from a wide range of fields attackedmilitary problems with a potent combination of empiricism andmathematical models. When airplanes came back riddled with holes fromenemy attacks, for instance, the intuitive response was to reinforcethe armor where the holes were. But, noted the scientists, those werethe planes that made it back. They didn't need more armor where theywere hit. The real challenge was to figure out the places that hadbeen hit in the planes that went down.

"It was a lively, informal, paradoxical exchange of ideas betweenamateur and professional war makers and it produced some brilliantsuccesses," wrote James R. Newman in The World of Mathematics,published in 1956, which cited O.R.'s role in simplifying supplylines, providing a quantitative basis for weapons evaluation, and so on.

But O.R. didn't live up to its postwar hype, its implicit promise to"solve everything." Militarily, it could attack certain tacticalproblems but, as the Vietnam War illustrated, O.R. wasn't the righttool for addressing strategic issues of where, or why, to fight. Evenfor mundane business questions, like how to design sales routes orwhat inventories to hold, O.R. specialists often lacked the data andcomputing power to turn their models into practical results. By the1970s, the Vietnam War had made O.R.'s military applications andPentagon funding suspect in universities, and businesses weregradually disbanding their O.R. groups.

For decades, the academic discipline retreated to theory. Scholarsbuilt their reputations on mathematical proofs, largely abandoningempiricism or real-world problem solving. Some O.R. veterans blame thepure-math imperialism common to many theory-based fields for this retreat.

"Some time in the 1970s or 1980s, O.R. was in a sense hijacked bymathematicians who insisted on imposing their view of rigorousmathematics onto the field. This placed much less emphasis on modelingand empirical work," says Richard C. Larson, a professor of civil andenvironmental engineering and engineering systems at MIT and for 15years the codirector of the institute's Operations Research Center,which recently celebrated its 50th anniversary. "In some OR journalstoday, the only empirical data are, `Date of submission' and `date ofacceptance."'

Other O.R. scholars argue that theory was the only way to advance thefield in a world of scarce data. "A paper would start, `Here is aninteresting problem. If I had all these data, this is what I couldhave done.' So the problem was challenging, but the focus was ontheory, because the data to support it did not exist," says DavidSimchi-Levi, a professor of engineering systems at MIT.

But in the 1990s, the data became available. Now corporate informationtechnology systems collect unprecedented amounts of data -- on costs,sales, and inventories, in itemized detail and real time. Wal-Mart andProcter & Gamble, for instance, know exactly how many 200-ouncebottles of liquid Tide Free have sold in which stores today. Thatinformation in turn determines how many new bottles are shipped fromwhich warehouse tomorrow.

. . .

Simchi-Levi exemplifies the new generation of O.R.scholar-practitioners. He entered the discipline as a theoreticalmathematician "focusing on algorithms and the theory behind differentlogistics problems," but was drawn into applications in 1992 when theNew York City school district called, looking for help with its busschedules.

Intrigued by the enormous potential of applying O.R. techniques tologistics problems, in 1995 he and his wife Edith, a softwaredeveloper, started a Chicago-based company called Logic Tools to applyO.R. techniques to supply-chain problems. Tweaking such mundane butstrategically critical decisions as where to site plants, when torestock, and so on, can provide enormous productivity boosts.

In his work, says Simchi-Levi, mathematical theory and businessapplications complement each other. "When I go to a company, or whenwe develop a new product," he says, "I am familiar with the state ofthe art in terms of engines and algorithms. For instance, theinventory positioning technology is very, very recent, even in academia."

As ubiquitous as it is invisible, O.R. is a crucial ingredient in theproductivity surge often credited to information technology. "The realdriver of the productivity resurgence that we've had since 1995 hasbeen the way the technology has allowed changes in business processesand the reorganization of work," says Erik Brynjolfsson, an MITeconomist. "For every dollar of [information technology] there are 9to 10 dollars of organizational change, human capital, and otherinvestments."

O.R. is only part of that story, since companies often have to makemajor organizational changes to reap its benefits. But without O.R.problem-solving, many management innovations couldn't take place.

"Having data doesn't give you productivity. Having better decisionsgives you productivity. So if O.R. is all about the science of makingbetter decisions, then this is clearly an area in which we'd like toclaim preeminence," says Michael Trick, a professor at the TepperSchool of Business at Carnegie-Mellon and the former president of theprofessional society INFORMS, the Institute for Operations Researchand the Management Sciences.

Trick's consulting projects include designing each year's AtlanticCoast Conference men's and women's basketball schedules. Arranging 16games among the nine men's teams may sound easy, but it requiressystematically sorting through hundreds of millions of possiblecombinations looking for the best way to satisfy dozens of conflictinggoals.

"You don't want to play too many consecutive home games. You don'twant to play too many consecutive away games. You have to make surethat every team has the same number of weekend home games," explainsTrick. "There are various games that have to be played -- Duke-NorthCarolina is always played on the same day. And then the TV networks,who are paying for all this, have strong views on how they would likegames to line up, so they can create a successful TV schedule. Youdon't want to have all the good games on the same weekend. You want tospread them out, so that every weekend there's a hot ACC game. Allthose things go into play."

Thomas L. Magnanti, the dean of engineering at MIT and previously thecodirector of the institute's Operations Research Center, isoptimistic about the field's future. Until recently, most O.R.scholars worked either in business schools, where the field is usuallycalled management science, or in departments of O.R. or industrialengineering. Now, he says, departments like mechanical engineering andelectrical engineering are hiring O.R. specialists.

Magnanti calls O.R. "a liberal education in a technological world."Just as a classical education once prepared students for a wide rangeof endeavors, from theology and science to diplomacy and warfare, heargues, so the habits and tools of O.R. are widely applicable tocontemporary problems.

"You can do finance today, manufacturing tomorrow, telecommunicationsthe day after. You can move from field to field and make contributionsthat have impact on all those fields," says Magnanti. "We do healthcare. We do criminal justice. You name it, we do it."

Virginia Postrel (www.dynamist.com) is author of The Substance ofStyle: How the Rise of Aesthetic Value Is Remaking Commerce, Culture,and Consciousness (HarperCollins).